Optimized streaming of large web 3D applications

In this paper, we present a web framework for optimizing the streaming of large 3D applications to allow an instant interaction independently from network bandwidth or available processing power of the rendering unit. Content that gets continuously refined is already state of the art for many web apps and improves the user experience. To also achieve this for web 3D applications, we combine the progressive transmission of geometry and texture data and additionally, we propose an overall rating function to control the priorities between different media transmission blocks. However, using streaming techniques usually results in low-quality visualizations of the 3D scenes until enough data has been loaded. Therefore, we introduce a novel method based on texture similarities that greatly reduces the amount of textures that must be transmitted while the visual quality of the scene remains almost the same even during loading.

[1]  Matthew G. Reyes,et al.  Structural texture similarity metrics for retrieval applications , 2008, 2008 15th IEEE International Conference on Image Processing.

[2]  Paul Grimm,et al.  Instant texture transmission using bandwidth-optimized progressive interlacing images , 2014, Web3D '14.

[3]  Amitabh Varshney,et al.  Variable-precision rendering , 2001, I3D '01.

[4]  Jinyuan Jia,et al.  A streaming framework for instant 3D rendering and interaction , 2015, VRST.

[5]  Paolo Cignoni,et al.  MeshLab: an Open-Source Mesh Processing Tool , 2008, Eurographics Italian Chapter Conference.

[6]  Shuang Liang,et al.  LPM: lightweight progressive meshes towards smooth transmission of Web3D media over internet , 2014, VRCAI '14.

[7]  Tobias Alexander Franke,et al.  Using images and explicit binary container for efficient and incremental delivery of declarative 3D scenes on the web , 2012, Web3D '12.

[8]  Guillaume Lavoué,et al.  Streaming compressed 3D data on the web using JavaScript and WebGL , 2013, Web3D '13.

[9]  Hugues Hoppe,et al.  Progressive meshes , 1996, SIGGRAPH.

[10]  Marc Alexa,et al.  The POP Buffer: Rapid Progressive Clustering by Geometry Quantization , 2013, Comput. Graph. Forum.

[11]  David L. Neuhoff,et al.  Structural similarity metrics for texture analysis and retrieval , 2009, 2009 16th IEEE International Conference on Image Processing (ICIP).

[12]  Christopher Schwartz,et al.  Level‐of‐Detail Streaming and Rendering using Bidirectional Sparse Virtual Texture Functions , 2013, Comput. Graph. Forum.

[13]  Paul Grimm,et al.  Efficient Image Distribution on the Web - Instant Texturing for Collaborative Visualization of Virtual Environments , 2015, GRAPP.

[14]  Günther Greiner,et al.  Adaptive Level-of-Precision for GPU-Rendering , 2011, VMV.